scholarly journals ALSgeneScanner: a pipeline for the analysis and interpretation of DNA NGS data of ALS patients

2018 ◽  
Author(s):  
Alfredo Iacoangeli ◽  
Ahmad Al Khleifat ◽  
William Sproviero ◽  
Aleksey Shatunov ◽  
Ashley R Jones ◽  
...  
Keyword(s):  
Motor Neurons ◽  
Health Care Professionals ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
Whole Exome ◽  
Exome Sequence Data ◽  
Als Patients ◽  
Ngs Data

AbstractAmyotrophic lateral sclerosis (ALS, MND) is a neurodegenerative disease of upper and lower motor neurons resulting in death from neuromuscular respiratory failure, typically within two years of first symptoms. Genetic factors are an important cause of ALS, with variants in more than 25 genes having strong evidence, and weaker evidence available for variants in more than 120 genes. With the increasing availability of Next-Generation sequencing data, non-specialists, including health care professionals and patients, are obtaining their genomic information without a corresponding ability to analyse and interpret it. Furthermore, the relevance of novel or existing variants in ALS genes is not always apparent. Here we present ALSgeneScanner, a tool that is easy to install and use, able to provide an automatic, detailed, annotated report, on a list of ALS genes from whole genome sequence data in a few hours and whole exome sequence data in about one hour on a readily available mid-range computer. This will be of value to non-specialists and aid in the interpretation of the relevance of novel and existing variants identified in DNA sequencing data.

scholarly journals Finding functional disease-associated non-coding variation using next-generation sequencing

2016 ◽  
Author(s):  
Paolo Devanna ◽  
Xiaowei Sylvia Chen ◽  
Joses Ho ◽  
Dario Gajewski ◽  
Alessandro Gialluisi ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Binding Sites ◽  
Large Scale ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Next Generation Sequencing Data ◽  
Whole Genome ◽  
Next Generation ◽  
Whole Exome ◽  
Generation Sequencing

ABSTRACTNext generation sequencing has opened the way for the large scale interrogation of cohorts at the whole exome, or whole genome level. Currently, the field largely focuses on potential disease causing variants that fall within coding sequences and that are predicted to cause protein sequence changes, generally discarding non-coding variants. However non-coding DNA makes up ~98% of the genome and contains a range of sequences essential for controlling the expression of protein coding genes. Thus, potentially causative non-coding variation is currently being overlooked. To address this, we have designed an approach to assess variation in one class of non-coding regulatory DNA; the 3′UTRome. Variants in the 3'UTR region of genes are of particular interest because 3'UTRs are responsible for modulating protein expression levels via their interactions with microRNAs. Furthermore they are amenable to large scale analysis as 3′UTR-microRNA interactions are based on complementary base pairing and as such can be predicted in silico at the genome-wide level. We report a strategy for identifying and functionally testing variants in microRNA binding sites within the 3'UTRome and demonstrate the efficacy of this pipeline in a cohort of language impaired children. Using whole exome sequence data from 43 probands, we extracted variants that lay within 3'UTR microRNA binding sites. We identified a common variant (SNP) in a microRNA binding site and found this SNP to be associated with an endophenotype of language impairment (non-word repetition). We showed that this variant disrupted microRNA regulation in cells and was linked to altered gene expression in the brain, suggesting it may represent a risk factor contributing to SLI. This work demonstrates that biologically relevant variants are currently being under-investigated despite the wealth of next-generation sequencing data available and presents a simple strategy for interrogating non-coding regions of the genome. We propose that this strategy should be routinely applied to whole exome and whole genome sequence data in order to broaden our understanding of how non-coding genetic variation underlies complex phenotypes such as neurodevelopmental disorders.

scholarly journals Poking COVID-19: insights on genomic constraints among immune-related genes between Qatari and Italian populations

2021 ◽  
Author(s):  
Hamdi Mbarek ◽  
Massimiliano Cocca ◽  
Yasser Al Sarraj ◽  
Chadi Saad ◽  
Massimo Mezzavilla ◽  
...  
Keyword(s):  
Innate Immunity ◽  
Sequence Data ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Host Pathogen Interaction ◽  
Whole Exome ◽  
Exome Sequence Data ◽  
Host Pathogen ◽  
Immune Related Genes ◽  
Exome Sequence

AbstractHost genomic information, specifically genomic variations, may characterize susceptibility to disease and identify people with a higher risk of harm, leading to better targeting of care and vaccination. Italy was the epicentre for the spread of COVID-19 in Europe, the first country to go into a national lockdown and has one of the highest COVID-19 associated mortality rates. Qatar, on the other hand has a very low mortality rate. In this study, we compared whole-genome sequencing data of 14398 adults and Qatari-national to 925 Italian individuals. We also included in the comparison whole-exome sequence data from 189 Italian laboratory confirmed COVID-19 cases. We focused our study on a curated list of 3619 candidate genes involved in innate immunity and host-pathogen interaction. Two population-gene metric scores, the Delta Singleton-Cohort variant score (DSC) and Sum Singleton-Cohort variant score (SSC), were applied to estimate the presence of selective constraints in the Qatari population and in the Italian cohorts. Results based on DSC SSC metrics demonstrated a different selective pressure on three genes (MUC5AC, ABCA7, FLNA) between Qatari and Italian populations. This study highlighted the genetic differences between Qatari and Italian populations and identified a subset of genes involved in innate immunity and host-pathogen interaction.

scholarly journals Poking COVID-19: Insights on Genomic Constraints among Immune-Related Genes between Qatari and Italian Populations

Genes ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1842
Author(s):  
Hamdi Mbarek ◽  
Massimiliano Cocca ◽  
Yasser Al-Sarraj ◽  
Chadi Saad ◽  
Massimo Mezzavilla ◽  
...  
Keyword(s):  
Innate Immunity ◽  
Sequence Data ◽  
Whole Genome Sequencing Data ◽  
Sequencing Data ◽  
Host Pathogen Interaction ◽  
Whole Exome ◽  
Exome Sequence Data ◽  
Host Pathogen ◽  
Immune Related Genes ◽  
Exome Sequence

Host genomic information, specifically genomic variations, may characterize susceptibility to disease and identify people with a higher risk of harm, leading to better targeting of care and vaccination. Italy was the epicentre for the spread of COVID-19 in Europe, the first country to go into a national lockdown and has one of the highest COVID-19 associated mortality rates. Qatar, on the other hand has a very low mortality rate. In this study, we compared whole-genome sequencing data of 14398 adults and Qatari-national to 925 Italian individuals. We also included in the comparison whole-exome sequence data from 189 Italian laboratory-confirmed COVID-19 cases. We focused our study on a curated list of 3619 candidate genes involved in innate immunity and host-pathogen interaction. Two population-gene metric scores, the Delta Singleton-Cohort variant score (DSC) and Sum Singleton-Cohort variant score (SSC), were applied to estimate the presence of selective constraints in the Qatari population and in the Italian cohorts. Results based on DSC and SSC metrics demonstrated a different selective pressure on three genes (MUC5AC, ABCA7, FLNA) between Qatari and Italian populations. This study highlighted the genetic differences between Qatari and Italian populations and identified a subset of genes involved in innate immunity and host-pathogen interaction.

scholarly journals Training workshop on Mycobacterium whole genome sequence data analysis

2019 ◽  
Vol 24 ◽  
Author(s):  
Yonas Kassahun Hirutu ◽  
Mesert D Bayeleygne ◽  
Adey F Desta ◽  
Tewodros Tariku ◽  
Markos Abebe
Keyword(s):  
Life Science ◽  
Sequence Data ◽  
Addis Ababa ◽  
Whole Genome Sequence ◽  
Next Generation Sequencing Data ◽  
Whole Genome ◽  
Training Workshop ◽  
Sequencing Data ◽  
Training Initiative ◽  
Generation Sequencing

Basic bioinformatics training workshop conducted at Armauer Hansen Research Institute (AHRI), Addis Ababa, Ethiopia. This report describes a bioinformatics training initiative started at AHRI aiming to support life science researchers and postgraduates in handling next-generation sequencing data.

scholarly journals NGSremix: A software tool for estimating pairwise relatedness between admixed individuals from next-generation sequencing data

2021 ◽  
Author(s):  
Anne Krogh Nøhr ◽  
Kristian Hanghøj ◽  
Genis Garcia Erill ◽  
Zilong Li ◽  
Ida Moltke ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Genetic Research ◽  
Likelihood Estimation ◽  
Software Tool ◽  
Estimation Methods ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Ngs Data ◽  
Generation Sequencing

Abstract Estimation of relatedness between pairs of individuals is important in many genetic research areas. When estimating relatedness, it is important to account for admixture if this is present. However, the methods that can account for admixture are all based on genotype data as input, which is a problem for low-depth next-generation sequencing (NGS) data from which genotypes are called with high uncertainty. Here we present a software tool, NGSremix, for maximum likelihood estimation of relatedness between pairs of admixed individuals from low-depth NGS data, which takes the uncertainty of the genotypes into account via genotype likelihoods. Using both simulated and real NGS data for admixed individuals with an average depth of 4x or below we show that our method works well and clearly outperforms all the commonly used state-of-the-art relatedness estimation methods PLINK, KING, relateAdmix, and ngsRelate that all perform quite poorly. Hence, NGSremix is a useful new tool for estimating relatedness in admixed populations from low-depth NGS data. NGSremix is implemented in C/C ++ in a multi-threaded software and is freely available on Github https://github.com/KHanghoj/NGSremix.

scholarly journals Inferring species compositions of complex fungal communities from long- and short-read sequence data

2021 ◽  
Author(s):  
Yiheng Hu ◽  
Laszlo Irinyi ◽  
Minh Thuy Vi Hoang ◽  
Tavish Eenjes ◽  
Abigail Graetz ◽  
...  
Keyword(s):  
Community Composition ◽  
Pathogen Detection ◽  
High Throughput Sequencing ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Composition Analysis ◽  
Sequencing Data ◽  
Species Classification ◽  
Shotgun Metagenomics ◽  
Query Coverage

Background: The kingdom fungi is crucial for life on earth and is highly diverse. Yet fungi are challenging to characterize. They can be difficult to culture and may be morphologically indistinct in culture. They can have complex genomes of over 1 Gb in size and are still underrepresented in whole genome sequence databases. Overall their description and analysis lags far behind other microbes such as bacteria. At the same time, classification of species via high throughput sequencing without prior purification is increasingly becoming the norm for pathogen detection, microbiome studies, and environmental monitoring. However, standardized procedures for characterizing unknown fungi from complex sequencing data have not yet been established. Results: We compared different metagenomics sequencing and analysis strategies for the identification of fungal species. Using two fungal mock communities of 44 phylogenetically diverse species, we compared species classification and community composition analysis pipelines using shotgun metagenomics and amplicon sequencing data generated from both short and long read sequencing technologies. We show that regardless of the sequencing methodology used, the highest accuracy of species identification was achieved by sequence alignment against a fungi-specific database. During the assessment of classification algorithms, we found that applying cut-offs to the query coverage of each read or contig significantly improved the classification accuracy and community composition analysis without significant data loss. Conclusion: Overall, our study expands the toolkit for identifying fungi by improving sequence-based fungal classification, and provides a practical guide for the design of metagenomics analyses.

scholarly journals Multi-gene incongruence consistent with hybridisation in Cladocopium (Symbiodiniaceae), an ecologically important genus of coral reef symbionts

2019 ◽  
Author(s):  
Joshua I Brian ◽  
Simon K Davy ◽  
Shaun P Wilkinson
Keyword(s):  
Sequence Data ◽  
Incomplete Lineage Sorting ◽  
Reticulate Evolution ◽  
Next Generation Sequencing Data ◽  
Putative Hybrid ◽  
Its2 Region ◽  
Sequencing Data ◽  
Lineage Sorting ◽  
Evolutionary Potential ◽  
Unbiased Test

Coral reefs rely on their intracellular dinoflagellate symbionts (family Symbiodiniaceae) for nutritional provision in nutrient-poor waters, yet this association is threatened by thermally stressful conditions. Despite this, the evolutionary potential of these symbionts remains poorly characterised. In this study, we tested the potential for divergent Symbiodiniaceae types to sexually reproduce (i.e. hybridise) within Cladocopium, the most ecologically prevalent genus in this family. With sequence data from three organelles (cob gene, mitochondria; psbAncr region, chloroplast; and ITS2 region, nucleus), we utilised the Incongruence Length Difference test, Approximately Unbiased test, tree hybridisation analyses and visual inspection of raw data in stepwise fashion to highlight incongruences between organelles, and thus provide evidence of reticulate evolution. Using this approach, we identified three putative hybrid Cladocopium samples among the 158 analysed, at two of the seven sites sampled. These samples were identified as the common Cladocopium types C40 or C1 with respect to the mitochondria and chloroplasts, but the rarer types C3z, C3u and C1# with respect to their nuclear identity. These five Cladocopium types have previously been confirmed as evolutionarily distinct and were also recovered in non-incongruent samples multiple times, which is strongly suggestive that they sexually reproduced to produce the incongruent samples. A concomitant inspection of Next Generation Sequencing data for these samples suggests that other plausible explanations, such as incomplete lineage sorting, are much less likely. The approach taken in this study allows incongruences between gene regions to be identified with confidence, and brings new light to the evolutionary potential within Symbiodiniaceae.

scholarly journals ScaleQC: a scalable lossy to lossless solution for NGS data compression

2020 ◽  
Vol 36 (17) ◽  
pp. 4551-4559 ◽  
Author(s):  
Rongshan Yu ◽  
Wenxian Yang
Keyword(s):  
Lossless Compression ◽  
Supplementary Information ◽  
Next Generation Sequencing Data ◽  
Sequencing Data ◽  
Source Codes ◽  
Compression Performance ◽  
Data Rates ◽  
Quality Value ◽  
Ngs Data ◽  
Bit Stream

Abstract Motivation Per-base quality values in Next Generation Sequencing data take a significant portion of storage even after compression. Lossy compression technologies could further reduce the space used by quality values. However, in many applications, lossless compression is still desired. Hence, sequencing data in multiple file formats have to be prepared for different applications. Results We developed a scalable lossy to lossless compression solution for quality values named ScaleQC (Scalable Quality value Compression). ScaleQC is able to provide the so-called bit-stream level scalability that the losslessly compressed bit-stream by ScaleQC can be further truncated to lower data rates without incurring an expensive transcoding operation. Despite its scalability, ScaleQC still achieves comparable compression performance at both lossless and lossy data rates compared to the existing lossless or lossy compressors. Availability and implementation ScaleQC has been integrated with SAMtools as a special quality value encoding mode for CRAM. Its source codes can be obtained from our integrated SAMtools (https://github.com/xmuyulab/samtools) with dependency on integrated HTSlib (https://github.com/xmuyulab/htslib). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Ethnically diverse urban transmission networks of Neisseria gonorrhoeae without evidence of HIV serosorting

2019 ◽  
Vol 96 (2) ◽  
pp. 106-109
Author(s):  
Jayshree Dave ◽  
John Paul ◽  
Thomas Joshua Pasvol ◽  
Andy Williams ◽  
Fiona Warburton ◽  
...  
Keyword(s):  
Neisseria Gonorrhoeae ◽  
Ethnic Groups ◽  
Antimicrobial Susceptibility ◽  
Sequence Data ◽  
Small Sample ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Sequencing Data ◽  
Transmission Networks ◽  
Hiv Serosorting

ObjectiveWe aimed to characterise gonorrhoea transmission patterns in a diverse urban population by linking genomic, epidemiological and antimicrobial susceptibility data.MethodsNeisseria gonorrhoeae isolates from patients attending sexual health clinics at Barts Health NHS Trust, London, UK, during an 11-month period underwent whole-genome sequencing and antimicrobial susceptibility testing. We combined laboratory and patient data to investigate the transmission network structure.ResultsOne hundred and fifty-eight isolates from 158 patients were available with associated descriptive data. One hundred and twenty-nine (82%) patients identified as male and 25 (16%) as female; four (3%) records lacked gender information. Self-described ethnicities were: 51 (32%) English/Welsh/Scottish; 33 (21%) white, other; 23 (15%) black British/black African/black, other; 12 (8%) Caribbean; 9 (6%) South Asian; 6 (4%) mixed ethnicity; and 10 (6%) other; data were missing for 14 (9%). Self-reported sexual orientations were 82 (52%) men who have sex with men (MSM); 49 (31%) heterosexual; 2 (1%) bisexual; data were missing for 25 individuals. Twenty-two (14%) patients were HIV positive. Whole-genome sequence data were generated for 151 isolates, which linked 75 (50%) patients to at least one other case. Using sequencing data, we found no evidence of transmission networks related to specific ethnic groups (p=0.64) or of HIV serosorting (p=0.35). Of 82 MSM/bisexual patients with sequencing data, 45 (55%) belonged to clusters of ≥2 cases, compared with 16/44 (36%) heterosexuals with sequencing data (p=0.06).ConclusionWe demonstrate links between 50% of patients in transmission networks using a relatively small sample in a large cosmopolitan city. We found no evidence of HIV serosorting. Our results do not support assortative selectivity as an explanation for differences in gonorrhoea incidence between ethnic groups.

scholarly journals MTBseq: a comprehensive pipeline for whole genome sequence analysis of Mycobacterium tuberculosis complex isolates

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5895 ◽  
Author(s):  
Thomas Andreas Kohl ◽  
Christian Utpatel ◽  
Viola Schleusener ◽  
Maria Rosaria De Filippo ◽  
Patrick Beckert ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Mycobacterium Tuberculosis ◽  
Genome Sequence ◽  
Sequence Data ◽  
Whole Genome Sequence ◽  
Whole Genome Sequencing Data ◽  
Phylogenomic Analysis ◽  
Whole Genome ◽  
Sequencing Data ◽  
Desktop Computer

Analyzing whole-genome sequencing data of Mycobacterium tuberculosis complex (MTBC) isolates in a standardized workflow enables both comprehensive antibiotic resistance profiling and outbreak surveillance with highest resolution up to the identification of recent transmission chains. Here, we present MTBseq, a bioinformatics pipeline for next-generation genome sequence data analysis of MTBC isolates. Employing a reference mapping based workflow, MTBseq reports detected variant positions annotated with known association to antibiotic resistance and performs a lineage classification based on phylogenetic single nucleotide polymorphisms (SNPs). When comparing multiple datasets, MTBseq provides a joint list of variants and a FASTA alignment of SNP positions for use in phylogenomic analysis, and identifies groups of related isolates. The pipeline is customizable, expandable and can be used on a desktop computer or laptop without any internet connection, ensuring mobile usage and data security. MTBseq and accompanying documentation is available from https://github.com/ngs-fzb/MTBseq_source.

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